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作者(中文):張亦嘉
作者(外文):Chang, Yi-Chia
論文名稱(中文):應用於防毒面具設計之頭臉人體計測分析
論文名稱(外文):The Head and Facial Anthropometric Analysis for Respirator Design
指導教授(中文):張堅琦
指導教授(外文):Chang, Chien-Chi
口試委員(中文):石裕川
林昱呈
口試委員(外文):Shih, Yuh-Chuan
Lin, Yu-Cheng
學位類別:碩士
校院名稱:國立清華大學
系所名稱:工業工程與工程管理學系
學號:108034570
出版年(民國):110
畢業學年度:109
語文別:中文
論文頁數:107
中文關鍵詞:人體計測調查防毒面具頭臉維度主成分分析集群分析尺寸分級
外文關鍵詞:Anthropometric SurveyMilitary RespiratorHead and Facial DimensionsPrincipal Component AnalysisCluster AnalysisSizing System
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防毒面具常用以降低軍事人員在任務行動中受傷和死亡的風險。佩戴防毒面具可使使用者免於受到有害物質的影響。防毒面具尺寸的設計與製造優良與否,影響防毒面具與佩戴者的貼合度及佩戴者感受的舒適性,而其設計和製造與人體頭臉之計測數據息息相關。臺灣在幾十年前量測之頭臉相關維度數據,不但仍使用於現今軍事護具上,且用於軍事防毒面具尺寸系統的建置。過去幾年中,軍隊的人口統計數據可能產生改變,因此本研究對舊有之數據是否適用於發展新一代之防毒面具存疑。此研究之目的為:(1)透過人體頭臉計測維度數據庫,整理臺灣男性現役軍人之頭臉部維度計測數據;(2)根據防毒面具相關之頭臉維度數據,透過主成分分析(Principal Component Analysis, PCA)歸納出關鍵維度,再使用兩階段分群法分析受測者之頭臉型,進而將之分群;(3)透過改良尺寸分級系統,重新訂定一套防毒面具尺寸系統。
本研究提取數據庫中448名臺灣男性現役軍人作為本研究之分析對象。該數據庫之施測者透過三維頭型掃描儀,量測受測者共23項防毒面具相關之頭臉部重要維度數據。透過主成分分析,本研究選擇7項主成分,以說明臺灣男性現役軍人的75.97%頭臉特徵解釋變異量,而代表主成分之7項關鍵維度如下:「左耳珠至右耳珠(經鼻下點)」、「鼻長(投影距離)」、「下臉長」、「左右耳珠至頭頂」、「兩眼內角間距弧長」、「鼻高(直線距離)」及「嘴寬」。兩階段分群法的第1階段,可以將受測者之頭臉數據分為4群。第2階段分析則是將每項單一數據歸納入4群。每項分群內的特徵在於其頭臉關鍵維度之叢集中心,而4群命名分別如下:「突鼻小頭臉」、「突鼻大頭臉」、「突鼻中頭臉」以及「扁鼻中頭臉」。藉由尺寸分級系統之重要維度「臉寬」及「臉長」,平移過去已建立之防毒面具尺寸分級系統,新建立專屬臺灣男性現役軍人之防毒面具尺寸分級系統,且此尺寸分級系統之涵蓋率可達98.88%。這項研究更提供測量數據的統計方法,用於描述臺灣軍用防毒面具男性現役軍人使用者之人體計測資料及其相關應用。
Military personnel rely on respirators to reduce risk of injury and death. Wearing a respirator can protect users from harmful substances. The design and manufacture respirator size affect the fit degree of users and the comfort, which relate to the head and facial anthropometry. In Taiwan, the anthropometric database generated decades ago is still in use today and comprise the comprehensive information available for the military respirator sizing system. The demographics of the Taiwanese military have changed over the last years, and there is concern over the applicability of the present data for use in fitting respirators. To fill this gap, the objectives were to:(1)analyze the head and facial anthropometric data based on the anthropometric database of Taiwanese military respirator male users;(2)use the respirator related database to identify the key dimensions by Principal Component Analysis(PCA) and then to categorize the clusters based on the Two-Staged Cluster Analysis; and(3)to improve the sizing system to re-determine a respirator sizing system.
A total of 448 Taiwanese military male head and facial data were selected from a database. In addition to height and weight, twenty-three head and facial dimensions were measured using a three-dimensional scanner. The PCA results revealed the selection of 7 components is adequate to explain the cumulatively accounted for 75.97% of total variance between the head and facial anthropometric dimensions of male users. The key dimensions as the representative variable of each principal component were as follows: Bitragion-Subnasale Arc, Nose Height, Menton-Subnasale Length, Bitragion Coronal Arc, Endocanthion Arc, Nose Protrusion and Lip Length. The first stage cluster analysis indicated that the head and facial dimensions of Taiwanese military males could be grouped into 4 clusters. The second stage cluster analysis categorized the individuals into 4 clusters. Each cluster was characterized by its centroid data for head and facial key dimensions, the clusters were individually named as: Pro-Nose Small-Head and Face, Pro-Nose Big-Head and Face, Pro-Nose Mid-Head and Face, and Flat-Nose Mid-Head and Face. By determining two important dimensions(Face Breadth and Face Length), this study created a new respirator sizing system that can cover at least 98.88% of all participants. This study also presents the summary statistics of the measurement data for describing the anthropometric variability of the current Taiwanese military respirator male users.
摘要 i
Abstract iii
致謝 v
目錄 vi
表目錄 ix
圖目錄 xii
第一章 緒論 1
1.1. 研究背景與動機 1
1.2. 研究目的 2
1.3. 研究架構 3
第二章 文獻探討 5
2.1. 防毒面具的介紹 5
2.2. 人體計測資料庫的建置與量測 7
2.2. 1. 各國人體計測資料庫的建置與量測 7
2.2. 2. 臺灣目前人體計測資料庫的建置與量測 9
2.3. 影響人體計測數據差異之變因 10
2.3. 1. 不同時間下造成之人體計測數據差異 10
2.3. 2. 不同人種間造成之人體計測數據差異 11
2.3. 3. 不同地區間造成之人體計測數據差異 13
2.3. 4. 不同職業間造成之人體計測數據差異 15
2.4. 統計方法 16
2.4. 1. 主成分分析 16
2.4. 2. 兩階段分群法 17
2.5. 防毒面具尺寸分級系統 18
2.5. 1. 洛斯阿拉莫斯國家實驗室建立之防毒面具尺寸分級系統 18
2.5. 2. 美國國家職業安全衛生研究所建立之防毒面具尺寸分級系統 21
2.5. 3. 其他研究建立之頭臉尺寸分級系統 25
2.6. 文獻小結 28
第三章 研究方法 30
3.1. 本研究所採用之頭臉數據庫之相關描述 30
3.2. 頭臉維度數據 33
3.2.1. 受測者數據 33
3.2.2. 標記點的選定 33
3.2.3. 量測項目的選定 35
3.3. 頭臉維度數據特徵分析流程 45
3.4. 防毒面具尺寸分級系統建置流程 48
第四章 研究結果 50
4.1. 頭臉維度數據分析 50
4.1.1. 頭臉維度數據之敘述性統計 50
4.1.2. 頭臉維度數據之主成分分析 50
4.2. 頭臉型分群 55
4.3. 防毒面具尺寸分級系統 66
4.3.1 使用LANL尺寸分級系統 66
4.3.2 使用NIOSH尺寸分級系統 68
4.3.3 新建防毒面具尺寸分級系統 69
4.3.4 新建防毒面具尺寸分級系統與頭臉分群結果 74
第五章 研究討論 79
5.1. 頭臉維度數據比較 79
5.2. 頭臉型分群比較 83
5.3. 防毒面具尺寸分級系統比較 84
5.4. 應用至防毒面具設計 87
第六章 結論與建議 89
6.1. 結論與建議 89
6.2. 限制 90
參考文獻 92
附錄一、本研究參考許涵慈(2018)之頭臉標記點及其定義 99
附錄二、本研究參考許涵慈(2018)使用之48頭臉維度定義 101
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